Welcome to

CIS 680

Term: Fall 2019

Location: Annenberg, ANNS 111

Time: Monday & Wednesday, 12:00 PM - 1:30 PM

Course Instructor

Dr. Jianbo Shi

Email: jshi@seas.upenn.edu Office: 466 Levine Hall

Course Description

CIS680 is a graduate seminar in advanced work on machine perception as it applies to robots as well as to the modeling of human perception.

Prerequisites: Prior experience in computer vision through courses such as CIS580, CIS581, or similar.

Course work:

  • 4 homeworks are expected
  • Final course project
  • Possible midterm

Late Policy: 20% reduction per day on the assignment. 5 free late days throughout the course. (not per assignment, for the whole course)


Piazza: https://piazza.com/class/jzvlwtgpg7t76i

Gradescope (report and code turn in): https://www.gradescope.com/courses/61693

Gradescope Entry Code: 9PKJDZ


Office Hours

Two group office hours are offered to help speed debugging and encourage collaboration. Some weeks we may only host one due to time constraints of the TAs. Check back here each week to check.

Location: GRASP Bump Space (4th floor Levine)

Time: Tuesday 9-11am

Location: GRASP Bump Space (4th floor Levine)

Time: Friday 9-11am

Teaching Assistants

Ken Chaney

Email: chaneyk@seas.upenn.edu

Nikos Kolotouros

Email: nkolot@seas.upenn.edu

Bernadette Bucher

Email: bucherb@seas.upenn.edu

Evangelos Chatzipantazis

Email: vaghat@seas.upenn.edu

Lingzhi Zhang

Email: zlz@seas.upenn.edu

Ty Nguyen

Email: tynguyen@seas.upenn.edu

Seungwon Lee

Email: leeswon@seas.upenn.edu

Code of Academic Integrity

University of Pennsylvania's CIS department encourages collaboration among graduate students. However, it is important to recognize the distinction between collaboration and cheating, which is prohibited and carries serious consequences. Cheating may be defined as using or attempting to use unauthorized assistance, material, or study aids in academic work or examinations. Some examples of cheating are: collaborating on a take-home exam or homework unless explicitly allowed; copying homework; handing in someone else's work as your own; and plagiarism. Any student suspected of cheating will be reported to the Office of Student Conduct.